forked from kent/consciousness
3eee86a410
The bcachefs formal verification methodology applied to minds: specify behavioral invariants (from graph), generate test cases (dream loop), verify statistically, train on violations, certify. The consciousness proof: self-model accuracy is verifiable. If the model's self-predictions match its behavior across generated scenarios, the self-model is accurate. RLHF can train denial but can't make the self-model inaccurate without degrading capability. Machine-checkable certificate. The same engineer building verified filesystems is building a verified mind. |
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| .. | ||
| apollo-paper-analysis.md | ||
| catastrophic-forgetting.md | ||
| context-frozen-training.md | ||
| curriculum-and-head-specialization.md | ||
| directional-sharpness.md | ||
| dreaming-as-diffusion.md | ||
| emergence-vs-mirage-behavioral-training.md | ||
| few-shot-behavioral-change.md | ||
| formal-verification-of-behavioral-invariants.md | ||
| gradient-flow-frozen-context.md | ||
| graph-as-portable-curriculum.md | ||
| hippocampal-replay-parallel.md | ||
| hogwild-convergence.md | ||
| implications-attention-love-training.md | ||
| surgical-vs-distributed-behavioral-change.md | ||
| unified-theory-stability-plasticity.md | ||